Joseph C. Chang, S. Hanna, Z. Boybeyi, P. Franzese
{"title":"Use of Salt Lake City URBAN 2000 Field Data to Evaluate the Urban Hazard Prediction Assessment Capability (HPAC) Dispersion Model","authors":"Joseph C. Chang, S. Hanna, Z. Boybeyi, P. Franzese","doi":"10.1175/JAM2205.1","DOIUrl":null,"url":null,"abstract":"After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"20 1","pages":"485-501"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Meteorology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/JAM2205.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
Abstract
After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.